radar

While flying cars have been a science fiction mainstay for decades, new sensors, software and other technology put personal air travel vehicles within reach. MEMS and Sensors Industry Group (MSIG) interviewed Dr. Alberto Speranzon, Fellow at Honeywell Aerospace Advanced Technology, about his upcoming keynote Sensors and Software Enabling Autonomy for Urban Air Mobility at the MEMS and Sensors Technical Congress (MSTC 2021) virtual event, April 13-15. Dr. Speranzon will discuss Honeywell’s challenges in enabling air taxis and the path forward to building out the necessary infrastructure. SEMI: People have dreamed of flying cars for decades. What has changed recently that makes them a near-term reality? Speranzon: There certainly are multiple factors that have contributed to pushing both new startups and established aerospace companies to make this dream a reality. Advances in battery technology are bringing electric aviation closer to being viable. There is still more to be done to achieve higher energy density in batteries, but already with today’s technology we can have vehicles that can fly from the suburbs to the downtown of a large U.S. city. At the same time, urbanization has created a lot of congestion, so finding new, efficient ways to move people and goods across megacities is becoming a critical need. Undeniably, the autonomous car industry has contributed to demonstrating that it is possible to achieve levels of automation and autonomy that were unimaginable just a few decades ago. The advances in sensing and computation required to make self-driving cars a reality is certainly going to help the aviation industry to develop autonomy in the air. SEMI: An air taxi must be highly sensorized. What types of sensors pose your biggest development challenge? Speranzon: Aircraft based on today’s battery systems simply cannot accommodate the size, power requirements and weight of sensors used by standard airliners. So there still is work to be done to reduce the SWaP (Size, Weight and Power) of these systems. Honeywell, for example, has developed a multipurpose radar, the IntuVue RDR-84K, that is only about the size of a paperback book. It can detect traffic, terrain and even weather, and was specially designed for air taxis and cargo UAS (unmanned aerial systems). Today, however, we still rely on human pilots to make the very complex decisions and, despite all the limitations that human eyes have, we do rely on them in a multitude of complex situations. There is also growing interest in integrating cameras into autonomous air taxis and similar platforms. Cameras can’t work alone, because they are affected by foggy, rainy and dim conditions. But they are lightweight, inexpensive, and require little power. That can make them very useful when combined with a compatible radar system like the RDR-84K. While these sensors bring new opportunities to the aerospace industry, they also pose some big challenges. For example, today’s state-of-the-art algorithms for image processing are machine learning algorithms called deep neural networks. They’re capable of extracting high-level information from pixels. But when it comes to aircraft certification, these algorithms face major hurdles. There is no software of this kind in any certified air vehicle, and it is unclear how regulators would certify neural network-based software components. Developers could avoid these new machine-learning algorithms and use standard computer vision methods instead. But they still face the challenge of deciding the type and quantities of images sufficient to declare the software “bug-free.” A similar set of questions will be also be true for radars, as they will be used to feed data more directly into the autonomy modules of future air taxis. So in the short term, we need to tackle the challenge of reducing the size and weight of sensors. But in parallel, we need to develop new ways to take advantage of machine learning: utilizing cameras and radars for autonomous decision making while still ensuring the highest standards of safety. SEMI: How is autonomous air mobility more or less challenging than autonomous ground vehicles? Speranzon: They are both challenging in their own ways. Autonomy on the ground – and I am thinking specifically of autonomous cars – is challenging as their “normal” behavior is very complex. We humans can drive from point A to point B over the public road network without a second thought. But to a machine, the heterogeneity of the people driving on the road, their sometimes unpredictable behavior, the changing weather conditions and shifting environments pose huge challenges. These things make what we call “normal driving” a very difficult problem to solve. At the same time, however, “off-nominal” scenarios in ground autonomy, while complex, are not orders of magnitude more complex than “nominal” scenarios. Ground vehicles can brake and stop, change lanes or move to the side of the road to avoid a crash or manage a malfunction. For autonomous air vehicles, the difference between nominal and off-nominal scenarios is more extreme. “Nominal” flying can rely on some of the existing aviation infrastructure, like communication between air traffic control and other aircraft. Air taxis can follow predefined paths and long-established aviation procedures as they move from vertiport A to vertiport B. This results in more automation than autonomy: everything is prescribed in advance and the onboard computer will follow what is pre-defined. Thus, nominal conditions will be fairly simple. However, in case of accidents or emergencies, aircraft face situations that are orders of magnitude more complex than nominal scenarios. An air vehicle cannot easily just “stop.” It could be 1,000-2,000 ft above ground, possibly above a bustling city. Human pilots go through rigorous training to be able to deal with emergencies like these. Consider the split-second judgments and airmanship behind the 2009 “miracle on the Hudson” landing. Asking autonomy to make the right decisions and execute emergency behaviors is a huge challenge. And these systems will need to be certified to the aviation industry’s very high standards. At present, we do not even have a well-established set of certification rules that an autonomous flying vehicle should comply with. SEMI: How soon might I be able to take an air taxi ride? Speranzon: Initial deployment of air taxis will happen around 2025. They will have human pilots but will use simpler interfaces than today’s cockpits. This first step will provide technologies that make it easier to take off and land, and to avoid traffic. That will reduce the need for highly experienced pilots and should help alleviate the overall shortage of pilots in the aviation industry. Fully autonomous air taxis are likely not going to show up until after 2030. In the beginning, they will likely fly only in regions where the weather is good most of the time. The autonomous car industry has already adopted this strategy, mostly deploying their technology in regions where the weather is dry and sunny. Soon, however, we’ll start seeing operations in “all-weather” scenarios and an increasing number of air vehicles within the same airspace. There is one critical stepping stone on the way to fully autonomous passenger aircraft: the success of fully autonomous cargo drones. For light parcels we will see initial deployments in 2022 or 2023, followed by larger UAS capable of transporting heaver cargo in 2024-2025. But whatever the timing, these are very exciting times. The aviation industry is witnessing a revolution with new vehicle manufacturers, new technologies and, likely, new applications we have not even dreamt of yet. Learn more about Honeywell’s work in urban air mobility and unmanned aircraft at aerospace.honeywell.com/uam. Alberto Speranzon is a Fellow within Honeywell Aerospace Advanced Technology. He received a Ph.D. in Electrical Engineering from the Royal Institute of Technology (KTH), Sweden in 2006. Since joining Honeywell, Alberto has been working on various aspects of autonomous systems for urban air mobility, leading such research areas as program manager and principal investigator. He is an IEEE Senior Member and a member of the Board of Governors of the IEEE Control Systems Society. Nishita Rao is product marketing manager at SEMI.

Part 2 of 2-part series on MSEC 2019 highlights. Read Part 1. Neural Networks on ChipTo be sure, low power is king when bringing machine learning to the sensor edge. Battery-powered, always-on sensing devices require it since frequent recharging is the death knell of any electronic product. That’s why semiconductor companies are offering new ways to conserve power.“MEMS sensor suppliers have made significant strides in the power, size and performance of their devices,” said Aspinity CEO Tom Doyle. “Yet these gains deliver only incremental power improvements to the system.”Doyle advocates a new architectural model that uses an analog neuromorphic processor to analyze all sensor data at the start of the signal chain instead of sending it downstream so power-hungry chips such as DSPs can digitize it before analysis.“The technology industry wants to take advantage of the many benefits of always-on sensing applications,” said Doyle. “Before we can reach mass proliferation, however, we need to resolve the power issues that are deal-breakers for some applications. We believe the answer to this challenge is architectural. All the data gathered by always-on sensing systems is analog in nature, yet as soon as it’s captured, it’s digitized immediately for analysis. Determining which data is important up front eliminates the digitization and processing of irrelevant data so that voice-first devices such as smart speakers and wearables/hearables can run for long periods of time without requiring battery recharge.”Syntiant CTO Jeremy Holleman agreed that on-device intelligence is the future.“Did you just fall? Is your heartrate a bit off? Deep learning provides a toolset that yields vastly superior decisions,” said Holleman. “The problem is that deep learning is computationally intensive. The answer is a neural network that performs on-device edge inferencing.”Holleman added that Syntiant’s neural decision processor was recently certified as Amazon Voice Service (AVS)-compliant for wake-word detection, making it easier to design voice control in battery-powered devices such as earbuds and wearables.MSEC Technology Showcase WinnerWith the groundswell of interest in intelligence at the edge, it was no surprise that Cartesiam won top honors among all competitors in the MSEC Technology Showcase for its NanoEdge AI, software that brings AI to the edge of the signal chain, making it easier for designers to create intelligent objects that can learn and understand.“Unlike other AI algorithmic technologies for sensing devices, NanoEdge enables both learning and inference at the edge, providing accurate and adaptive intelligence,” said Cartesiam Managing Director and Co-founder Marc Dupaquier, who accepted the award. “It’s also the only tool of its kind that does not require data scientists on board for implementation, which saves a tremendous amount of money. Our clients can build a machine learning library and embed it into their own code within weeks to realize the same caliber of unsupervised neural network that was once the exclusive domain of AI cloud vendors.”MSIG 2019 Hall of FameAt this year’s conference, MSIG Director Carmelo Sansone recognized two longtime contributors to the commercialization of MEMS and sensors: Peter G. Hartwell, Ph.D., chief technology officer at InvenSense, a TDK group company; and Thomas Kenny, professor and senior associate dean of engineering at Stanford University.Hartwell leads technology strategy and the InvenSense advanced technology research group. He has more than 25 years’ experience commercializing silicon MEMS products, including advanced sensors and actuators, and developing MEMS testing techniques.Kenny’s academic accomplishments include authoring or co-authoring more than 250 scientific papers and holding 50 issued patents. He has also advised more than 50 graduated Ph.D. students from Stanford.MSEC 2020Mark your calendar for next year’s MSEC, October 12-14, at Coronado Island Marriott Resort Spa in Coronado, Calif. Get updates from MSIG on MSEC and other upcoming events including MSTC 2020.Stay in Touch with MSIGMEMS Sensors Industry Group (MSIG), a SEMI Strategic Association Partner, is the industry association representing the global MEMS and sensors supply chain. To learn how MSIG enables professionals in the MEMS and sensors industry to innovate, address common challenges and accelerate business results, visit us today.Connect with MSIG on Twitter and LinkedIn. Subscribe to SEMI Blog: Technology and Trends.Maria Vetrano is a public relations consultant at SEMI.

Stefano Zanella, Head of Automotive, Industrial and Location Businesses, TDK InvenSense will present at next month’s SEMICON Taiwan (September 18-20, 2019 in Taipei City, Taiwan). SEMI Taiwan’s Emmy Yi spoke with Stefano for a preview of his talk.SEMI: What macro market trends are driving automotive manufacturers to increase the variety and volume of MEMS sensors in cars?Zanella: The car world is changing. Consumers increasingly view car ownership as less desirable, yet the number of miles traveled and of hours spent in a car are rising steadily. At the same time, cars are changing profoundly, and the pace of change is rapid. To thrive in this new world, automakers are becoming transportation enablers and providers.Many vehicles today autonomously interact with humans and the world around them, operate with less or no human control, and are powered by electric batteries. MEMS sensors – which mimic and augment the five human senses – are front and center in these advancements.Unlike other types of sensors – such as cameras, radar and GNSS/GPSS – MEMS gyroscopes are functional in every environment. Gyroscopes, as well as accelerometers, can supplement those other sensors when they are not available and boost the accuracy of their outputs when they are available. Both camera stabilization and dead reckoning when GNSS is unavailable are good examples of the latter. Other prevalent sensors include MEMS microphones, used to capture voice commands, ultrasonic sensors, which can be leveraged for parking and gesture recognition, and fingerprint sensors, which can improve car security.SEMI: How can automakers stay competitive in this changing landscape?Zanella: Automakers can future-proof their relevance in the transportation market in several ways. By embracing consumer migration toward ride-sharing over car ownership, many are transforming from manufacturers to mobility providers. Carmakers that invest in ride-sharing and other modes of transportation (e.g., scooters) can sustain their profitability, even if the number of vehicles sold eventually shrinks or simply doesn’t grow as much as anticipated.Automakers will need to pursue new avenues of product differentiation. Traditionally, automakers have kept performance and aesthetics to themselves by owning the engine and the body design of the car, leaving nearly everything else to suppliers. Autonomous driving and electrification, however, are pushing automakers to own the battery pack and the autonomous driving software stack.While we are just beginning to see standardization in battery packs, automakers are likely to own the autonomous driving stack for many years to come. Automakers that offer cars with highly functional and efficient batteries and driving stacks stand to gain market share.Automotive infotainment systems will become increasingly crucial as autonomous driving turns everyone into a passenger. Audio subsystem providers such as Harman Kardon, Bose, and Bang Olufsen, for example, jockeyed for attention at the most recent Geneva Motor Show, demonstrating sophisticated surround-sound systems that rival premium-quality home audio setups.With more and more consumers using voice interfaces to interact with devices in the home, drivers are less willing to accept spotty accuracy in the car. Hence, automakers are using more higher-performing MEMS microphones to accurately capture voice commands. This will come as a relief to those of us who routinely yell at our steering wheels while using voice command to try to call home. Demand for higher quality infotainment systems has prompted some automotive OEMs to own the entire infotainment system and work directly with sensor and chipmakers, a level of intimacy that gives automakers a chance to tune sensor and chip development to their own needs. This tighter relationship also positions device suppliers to forge more direct links with drivers.SEMI: Which MEMS sensors are particularly important to tomorrow’s automobiles and why?Zanella: For many years the automotive industry has been integrating more electronics into cars to improve safety, advance the driver and passenger experience, and, more recently, power the car. As vehicles rely less on human control, automakers must replace the senses of the driver with something else. That something else is a bunch of sensors, microphones, cameras, radar and LIDAR to replace vision and hearing.Since MEMS sensors such as accelerometers, gyroscopes and pressure sensors are much more robust than other types of sensors to operate in snow, rain and darkness and other imperfect environments, automakers use them to ensure that the vehicle never gets lost when other sensors and/or the GPS/GNSS signal become unavailable in tunnels or urban canyons. Gyros help determine direction, accelerometers velocity and distance driven, and pressure sensors height, such as when taking a fork on a multi-level highway. At the same time, fingerprint sensors, ultrasonic parking sensors, and temperature sensors are improving convenience, safety and security for the car’s occupants. Automakers increasingly use inertial and environmental sensors, MEMS microphones, fingerprint sensors, and vision/imaging sensors to augment or replace the five human senses on which car drivers have relied for over 100 years. Source: TDK InvenSense SEMI: To what degree can MEMS sensors enable automotive security?Zanella: MEMS sensors are used widely to enhance security today. Some of their mechanisms are easy to understand while some are unexpected. For instance, ultrasonic fingerprint sensors can authenticate the driver of a vehicle to prevent car theft or something less onerous, like a teenage driver taking the car out without permission.Accelerometers and gyroscopes can prevent a new type of spoof on keyless entry systems. Imagine that you are very close to your vehicle. Your car senses the remote control in your pocket and automatically opens the doors when you pull the handle. Now suppose that your car is parked on the street, not far from your house. You leave the remote control home, and the car doesn’t sense the proximity of the remote control. Great! No one can enter your car, unless ... a thief has a big signal amplifier that makes your car think that the keyless entry device is next to the car. In this case, what can an automaker do? Add an accelerometer that restricts the keyless device from broadcasting the entry signal unless you are walking to the car with the device on your person.SEMI: What would you like SEMICON Taiwan attendees to take away from your presentation?Zanella: I would like them to embrace the transformations afoot in the automotive market as well as their associated design challenges since, by overcoming these hurdles, they can offer significant societal benefits such as safer and cleaner transportation. At the same time, these transformations mean significant opportunities for semiconductor industry revenue growth. And while design-to-delivery cycles in automotive are longer than in consumer and mobile, the automotive market supports higher-value devices as well as the chance to fold dozens of MEMS sensors into a single model.To paraphrase Lord Kelvin: If you can’t sense it, you can’t manage it. As suppliers of many key technologies that make intelligent transportation possible, the MEMS sensors industry is in an excellent position to help automakers manage the many challenges ahead.Stefano Zanella, Ph.D., is Head of Automotive, Industrial and Location Businesses at TDK InvenSense, where he brings MEMS sensors (including accelerometers, gyroscopes and microphones) and location solutions to the automotive and industrial markets. Zanella holds an MS and a Ph.D. in Electrical Engineering from the University of Padova, Padova, Italy as well as MBAs from both the UC Berkeley Haas School of Business and from Columbia University.He will present MEMS Sensors Enabling the Smart Car Revolution on Wednesday, September 18, 2019, at SEMICON Taiwan at 1F 4F, Taipei Nangang Exhibition Center, Taipei City, Taiwan. Register today and save 20% to learn how MEMS sensors are transforming the human experience with cars.Connect with Stefano Zanella at SEMICON Taiwan or via LinkedIn. You can also get more information on TDK’s automotive solutions and application guides online.Interested in engaging with the MEMS sensors supply chain? SEMI MEMS Sensors Industry Group is a technology community that enables professionals in the MEMS and sensors industry to innovate, address common challenges and accelerate business results.Emmy Yi is a marketing specialist at SEMI Taiwan.

A short trip to Monterey, California provided an exciting glimpse into what is in store for the future. Along with 550 attendees and 60 exhibitors, I took a quick visit through the aisles and conference venue to find several exciting developments this year!So many exciting new products are on the horizon. Dr. Peter G. Hartwell, CTO of InvenSense, A TDK Group Company, provided a view future of the way sensors including optical, audio, balance, direction, location, and chemical will provide improvements over human capabilities. A glimpse into our future experiences with a 360-view winter wonderland experience of riding a snow mobile using two 180°C fisheye lens cameras with his presentation “Sensors: Where Reality Meets Virtual.” The only warning was that with so many cameras and social media privacy is lost!Dr. Hans Stork, CTO, ON Semiconductor discussed some of the recent investigations his company has made on the many LiDAR sensors. He enlightened listeners with more details of the optical/LiDAR Fusion with FUSE ONE that was unveiled at CES 2019. Future cars will have a combination of cameras, LiDAR, radar, and ultrasonics. No one sensor has it all. There are many companies offering LiDAR for automotive applications, but the products are still too expensive and the market will shake out over the next few years. Douglas Hackler, CEO, American Semiconductor presented the company’s achievement in flip chip on flex circuit assembly for a variety of applications, including pharmaceuticals, wearable wristbands, and IoT communications. Interconnects supported include ACA, ACF, advanced z-axis materials, and low temperature solder. He also described flexible hybrid electronics using printed electronics and a wafer CSP assembly for sensors. With this operation located in Idaho, products can be assembled in the U.S. Jean-Charles Souriau from CEA-Leti described the organization’s detailed research in developing in flip chip assembly on a flexible label with a thin die. A gold stud bump flip chip and thermo-compression bonding with glue is used to attach the die to a flex substrate. A polymer fabricated on thin glass was also demonstrated. Clearly, much progress has been made in flexible printed electronics in the last year with many presentations describing progress. Results of a benchmark study conducted at Cal Poly examined some of the key developments in bump materials and interconnect methods. Key areas such as antennas, batteries, PV and energy harvesting, a variety of sensors, and audio technology were investigated. Dr. Pradeep Lall presented work examining developments in conductive inks for 3D printed electronics.Dr. Subu Iyer and his student, Arsalan Alam, of UCLA presented some exciting research on heterogeneously integrated foldable display on elastomeric substrate, FlexTrate™, using vertically corrugated interconnects. This can be considered fan-out wafer level packaging. The work holds much promise for applications including foldable displays, wireless powered systems and surface electromyography systems. Fine pitch ≤40 micron interconnects bendable to 1 mm bending radius passed more than 6,000 bending cycles. Dr. Mark Poliks of Binghamton University described their work on the development of a wearable flexible hybrid electronics ECG monitor. While the work is in the early stages, human trials will soon begin and the results look promising. New materials will be key in the future products. Reliability test data was also presented on aerosol-jet printed traces on Upilex-S, including tensile, peel and bend testing, as well as “healing” of the damage. New product introductions included U.K’s Peratech’s EDGE force-sensing solution targeted form smartphones, wearables, and tablets. In this HMI solution, Peratech’s thin sensors are mechanically integrated into key areas of the smartphone to capture a user’s natural single-handed grip, ergonomic finger movements, intuitive pressure sand squeezes to control key functions. It even works with the users has wet hands or is wearing gloves! This eliminates the need for physical button openings and allows the implementation of a thinner, more contoured device with a rigid-metal chassis. Next year’s event will be in San Jose during the last week of February. Stay tuned to SEMI’s website for more details.Jan Vardaman is president and founder of TechSearch International, Inc., which has provided market research and technology trend analysis in semiconductor packaging since 1987. She is the co-author of How to Make IC Packages (by Nikkan Kogyo Shinbunsha), a columnist with Printed Circuit Design Fab/Circuits Assembly, and the author of numerous publications on emerging trends in semiconductor packaging and assembly. She is a senior member of IEEE EPS and is an IEEE EPS Distinguished Lecturer as well as a member of SEMI, SMTA, IMAPS, and MEPTEC.

Marcellino Gemelli, director of global business development at Bosch Sensortec, will present at the upcoming MEMS Sensors Executive Congress on October 29-30, 2018 in Napa, Calif. SEMI’s Maria Vetrano caught up with Gemelli to give MSEC attendees a preview of Gemelli’s feature presentation.Sensor fusion — the integration of different types of sensors through software algorithms to increase overall system performance and/or reduce power consumption— has come a long way since its inception. In those early days, sensor fusion generally involved MEMS inertial sensors only. The advent of new sensor varieties, including environmental sensors, is making new use cases a reality. Gemelli will explore the ways in which the next generation of sensor fusion is improving autonomous mobility devices. SEMI: Why are environmental sensors important to autonomous mobility devices?Gemelli: When most of us think of autonomous systems, we think that they are driven by motion sensors and proximity sensors (e.g., radar, Lidar). When vertical location comes into play, however, in applications such as drones or asset tracking, pressure sensors become an integral part of flight control, navigation and positioning in GPS-challenged areas.While not commonly considered an electronically enabled sense, the ability to “smell” the environment opens new opportunities. The quality of a user’s experience with personal cleaning robots and robo-taxis are good examples of where we might want to enable scent detection.SEMI: I’ve never thought much about using sensors to detect smell. How would a robo-taxi or a cleaning robot benefit from scent detection?Gemelli: Fully autonomous cars will inevitably give rise to robo-taxis. In fact, last month Volvo announced its fully electric robo-taxi, and in March 2018 Waymo announced that Jaguar Land Rover’s SUV would join Fiat Chrysler’s Chrysler Pacifica minivans in its planned fleet of robo-taxis, so we may see robo-taxis in the U.S. within the next five years.With robo-taxis fast-approaching, we need technologies that provide the same level of oversight that a taxi driver once fulfilled. Gas sensors would function like an electronic nose (e-nose) in a robo-taxi to inform the taxi’s owner of prohibited passenger behavior, such as eating, drinking or smoking in the vehicle, which could potentially damage the vehicle’s interior. Camera sensors could record the act as proof of the offense.Cleaning robots would be more sophisticated than they are today. In addition to leveraging image and range-finding sensors to more accurately map the rooms in your house, they could also detect scents from spilled red wine, pet urine or other foreign materials. When the cleaning robot, such as a vacuum, detects the foreign substance, it would navigate around the substance instead of going through it and spreading it all over the carpet.In addition to robo-taxis and cleaning robots, I will also discuss asset tracking and drones.SEMI: What role does sensor fusion play in autonomous mobility devices?Gemelli: Combining sensor fusion with artificial intelligence (AI) will generate new use cases and therefore new markets for sensor suppliers.There is another major benefit as well. With so many connected devices in our lives — including those with cameras, location awareness and always-listening capabilities — we are seeing growing concern about user privacy. Sensor fusion and AI can help to alleviate this concern: By supporting more local processing, they allow for greater control of data, safeguarding personal privacy.SEMI: Who is responsible for the AI part of the sensor-fusion equation?Gemelli: AI is a new frontier for MEMS and sensors suppliers. It benefits us and our customers to embrace AI algorithms through in-house development and/or partnerships.SEMI: What would you like MEMS Sensors Executive Congress attendees to take away from your presentation?Gemelli: I plan to issue a call to action to increase research in hybrid sensor-fusion software architectures, including AI, as suppliers’ collaboration will benefit the industry at large.Marcellino Gemelli is currently based in Palo Alto (CA) responsible for business development of Bosch Sensortec's MEMS product portfolio. He received the ‘Laurea’ degree in Electronic Engineering at the University of Pavia, Italy while in the Italian Army and an MBA from MIP, the Milano (Italy) Polytechnic business school. He previously held various engineering and product management positions at STMicroelectronics from 1995 to 2011 in the fields of MEMS, electronic design automation and data storage. He was contract professor for the Microelectronics course at the Milano (Italy) Polytechnic from 2000 to 2002.Marcellino Gemelli will present Environmental Sensors Systems Enabling Autonomous Mobility on Tuesday, October 30 at MEMS Sensors Executive Congress in Napa Valley, Calif.Register today to learn more about the connection between sensor fusion, AI and next-generation autonomous mobility devices.Maria Vetrano is a public relations consultant at SEMI.